Background: In the microarray experiment, many undesirable systematic variations are commonly observed. Normalization is the process of removing such variation that affects the me...
Dankyu Yoon, Sung-Gon Yi, Ju-Han Kim, Taesung Park
Inner holes, artifacts and blank spots are common in microarray images, but current image analysis methods do not pay them enough attention. We propose a new robust model-based me...
Qunhua Li, Chris Fraley, Roger Eugene Bumgarner, K...
A key challenge in the management of microarray data is the large size of images that constitute the output of microarray experiments. Therefore, only the expression values extrac...
Background: To cancel experimental variations, microarray data must be normalized prior to analysis. Where an appropriate model for statistical data distribution is available, a p...
Background: DNA microarrays, which have been increasingly used to monitor mRNA transcripts at a global level, can provide detailed insight into cellular processes involved in resp...
Tao Han, Cathy D. Melvin, Leming M. Shi, William S...